All posts in category Complexity Politics

On Tuesday, hundreds of thousands of people turned out in the streets of Ouagadougou to protest a plan to remove terms limits ahead of next year’s presidential election in Burkina Faso. Blaise Compaore has held that country’s top office for 27 years by way of a 1987 coup and four subsequent elections that have not been fair, and his party dominates the legislature for the same reason. Tuesday’s protests are part of a wider and ongoing wave of actions that includes a general strike and stay-aways from schools and universities. A similar wave of protests occurred over several months in 2011. The state’s efforts to repress those challenges killed several people on at least two occasions, and virtually nothing changed in their wake.

So, will the latest protests in Burkina Faso coalesce into a sustained campaign, or will they soon peter out? If they do coalesce, will that campaign spur significant reform or even revolution, or will it dissipate against repression, redirection, and resistance from incumbent power-holders?

The truth is, no one really knows, and this uncertainty is not specific to Burkina Faso. After decades of thoughtful research, social scientists still can’t reliably predict which bouts of unrest will blow up into revolutions and which won’t.

We can say some useful things about which structural conditions are more conducive, and thus which cases are more susceptible, to sustained popular challenges. A study I co-piloted with Erica Chenoweth (details forthcoming) found several features that can help assess where nonviolent campaigns are more likely to emerge, but the forecasting power of models based on those features is not stellar. Efforts to develop predictive models of civil-war onset have achieved similar results.

Once unrest starts to burble, though, we still don’t understand and can’t model the ensuing process well enough to reliably predict which way it will tip. Across many cases, a simple base-rate forecast will produce very accurate results. Keep betting on the persistence of the status quo, and you’ll almost always be right. If you’re trying to predict what will happen in a specific case at a specific juncture, however, it’s still hard to improve much on that crude baseline.

This persistent uncertainty can be maddening. Lots of smart people have spent a lot of time studying and thinking about these processes, and it feels like all that effort should have yielded bigger gains in predictive power by now.

That failure is also enlightening. If we believe that our efforts to date have been thoughtful and thorough, then the lack of progress on predicting the dynamics of these situations is telling something important about the nature of the underlying process. Uncertainty isn’t just a consequence of these political behaviors; it’s a prerequisite for them. As Phil Arena said on Twitter:

.@dtchimp There's good reason to think we *can't* get much past that, b/c if everyone knew who was willing to resort to violence & under +

And it’s not just uncertainty about the potential for harsh state repression, which is what I took Phil to mean by “violence.” Uncertainty about who else will turn out under what conditions, what forms that violence will take and exactly whom it will directly affect, how challengers will organize and adapt in response to those events, what changes in policy or institutions those actions will produce, and who will benefit or suffer how much from those changes are all relevant, too.

In short, the rare political “events” we wish to predict are shorthand for myriad interactions over time among large numbers of heterogeneous individuals who plan and learn and screw up in a changing environment in which information is inevitably incomplete and imperfect. The results are not random, but they are complex, in both the conventional and scientific sense of that term. If we could reliably foresee how things were going to go, then we would adapt our behavior accordingly, and the whole thing would unravel before it even started.

Under these conditions, central tendencies can and do still emerge. A small but growing body of work in political science shows that we can use structural patterns and observations of leading-edge activities to smudge base-rate forecasts a bit in either direction and achieve marginal gains in accuracy. Systems that properly elicit and combine forecasts from thoughtful crowds also turn out to have real predictive power, especially on short time horizons.

Still, the future trajectories of individual cases of incipient revolution will remain hard to foresee with accuracy much beyond the banal prediction that tomorrow will most likely resemble today. That persistent fuzziness is not always what politicians, activists, investors, and other interested or just curious observers want to hear, but on this class of events, it’s probably as clairvoyant as we’re going to get.

As citizens and as engaged intellectuals, we all have the right—indeed, an obligation—to make moral judgments and act based on those convictions. As political scientists, however, we have a unique set of potential contributions and constraints. Political scientists do not typically have anything of distinctive value to add to a chorus of moral condemnation or declarations of normative solidarity. What we do have, hopefully, is the methodological training, empirical knowledge and comparative insight to offer informed assessments about alternative courses of action on contentious issues. Our primary ethical commitment as political scientists, therefore must be to get the theory and the empirical evidence right, and to clearly communicate those findings to relevant audiences—however unpalatable or inconclusive they might be.

That’s a manifesto of sorts, nested in a great post by Marc Lynch at the Monkey Cage. Marc’s post focuses on analysis of the Middle East, but everything he writes generalizes to the whole discipline.

I’ve written a couple of posts on this theme, too:

“This Is Not a Drill,” on the challenges of doing what Marc proposes in the midst of fast-moving and politically charged events with weighty consequences; and

“Advocascience,” on the ways that researchers’ political and moral commitments shape our analyses, sometimes but not always intentionally.

Putting all of those pieces together, I’d say that I wholeheartedly agree with Marc in principle, but I also believe this is extremely difficult to do in practice. We can—and, I think, should—aspire to this posture, but we can never quite achieve it.

That applies to forecasting, too, by the way. Coincidentally, I saw this great bit this morning in the Letter from the Editors for a new special issue of The Appendix, on “futures of the past”:

Prediction is a political act. Imagined futures can be powerful tools for social change, but they can also reproduce the injustices of the present.

Concern about this possibility played a role in my decision to leave my old job, helping to produce forecasts of political instability around the world for private consumption by the U.S. government. It is also part of what attracts me to my current work on a public early-warning system for mass atrocities. By making the same forecasts available to all comers, I hope that we can mitigate that downside risk in an area where the immorality of the acts being considered is unambiguous.

The number of people displaced by violent conflict hit the highest level since World War II at the end of 2013, the head of the United Nations refugee agency, António Guterres, said in a report released on Friday…

Moreover, the impact of conflicts raging this year in Central African Republic, South Sudan, Ukraine and now Iraq threatens to push levels of displacement even higher by the end of 2014, he said.

…is, I think, another manifestation of the trends I discussed in a blog post here last September:

If we think on a systemic scale, it’s easier to see that we are now living through a period of global disorder matched in recent history only by the years surrounding the disintegration of the Soviet Union, and possibly exceeding it. Importantly, it’s not just the spate of state collapses through which this disorder becomes evident, but also the wider wave of protest activity and institutional transformation to which some of those collapses are connected.

If that’s true, then Mr. Guterres is probably right when he predicts that this will get even worse this year, because things still seem to be trending toward disorder. A lot of the transnational activity in response to local manifestations is still deliberately inflammatory (e.g., materiel and cash to rebels in Syria and Iraq, Russian support for separatists in Ukraine), and international efforts to quell some of those manifestations (e.g., UN PKOs in CAR and South Sudan) are struggling. Meanwhile, in what’s probably both a cause and an effect of these processes, global economic growth still has not rebounded as far or as fast as many had expected a year or two ago and remains uncertain and uneven.

In other words, the positive feedback still seems to be outrunning the negative feedback. Until that turns, the systemic processes driving (and being driven by) increased refugee flows will likely continue.

Addendum: The quote at the start of this post contains what I think is an error. A lot of the news stories on this report’s release used phrases like “displaced persons highest since World War II,” so I assumed that the U.N. report included the data on which that statement would be based. It turns out, though, that the report only makes a vague (and arguably misleading) reference to “the post-World War II era.” In fact, the U.N. does not have data to make comparisons on numbers of displaced persons prior to 1989. With the data it does have, the most the UNHCR can say is this, from p. 5: “The 2013 levels of forcible displacement were the highest since at least 1989, the first year that comprehensive statistics on global forced displacement existed.”

The picture also looks a little different from the press release if we adjust for increases in global population. Doing some rough math with the number of displaced persons in this UNHCR chart as the numerator and the U.S. Census Bureau’s mid-year estimates of world population as the denominator, here are some annual statistics on displaced persons as a share of the global population:

1989: 0.65%
1992: 0.84%
2010: 0.63%
2014: 0.72%

In no way do I mean to make light of what’s obviously a massive global problem, but as a share of the global population, the latest numbers are not (yet) even the worst since 1989, the first year for which UNHCR has comparable data.

Did you anticipate the Syrian uprising that began in 2011? What about the Tunisian, Egyptian, and Libyan uprisings that preceded and arguably shaped it? Did you anticipate that Assad would survive the first three years of civil war there, or that Iraq’s civil war would wax again as intensely as it has in the past few days?

All of these events or outcomes were difficult forecasting problems before they occurred, and many observers have been frank about their own surprise at many of them. At the same time, many of those same observers speak with confidence about the causes of those events. The invasion of Iraq in 2003 surely is or is not the cause of the now-raging civil war in that country. The absence of direct US or NATO military intervention in Syria is or is not to blame for continuation of that country’s civil war and the mass atrocities it has brought—and, by extension, the resurgence of civil war in Iraq.

But here’s the thing: strong causal claims require some confidence about how history would have unfolded in the absence of the cause of interest, and those counterfactual histories are no easier to get right than observed history was to anticipate.

Like all of the most interesting questions, what causality means and how we might demonstrate it will forever be matters for debate—see here on Daniel Little’s blog for an overview of that debate’s recent state—but most conceptions revolve around some idea of necessity. When we say X caused Y, we usually mean that had X not occurred, Y wouldn’t have happened, either. Subtler or less stringent versions might center on salience instead of necessity and insert a “probably” into the final phrase of the previous sentence, but the core idea is the same.

In nonexperimental social science, this logic implicitly obliges us to consider the various ways history might have unfolded in response to X’ rather than X. In a sense, then, both prediction and explanation are forecasting problems. They require us to imagine states of the world we have not seen and to connect them in plausible ways to to ones we have. If anything, the counterfactual predictions required for explanation are more frustrating epistemological problems than the true forecasts, because we will never get to see the outcome(s) against which we could assess the accuracy of our guesses.

As Robert Jervis pointed out in his contribution to a 1996 edited volume on counterfactual thought experiments in world politics, counterfactuals are (or should be) especially hard to construct—and thus causal claims especially hard to make—when the causal processes of interest involve systems. For Jervis,

A system exists when elements or units are interconnected so that the system has emergent properties—i.e., its characteristics and behavior canot be inferred from the characteristics and behavior of the units taken individually—and when changes in one unit or the relationship between any two of them produce ramifying alterations in other units or relationships.

As Jervis notes,

A great deal of thinking about causation…is based on comparing two situations that are the same in all ways except one. Any differences in the outcome, whether actual or expected…can be attributed to the difference in the state of the one element…

Under many circumstances, this method is powerful and appropriate. But it runs into serious problems when we are dealing with systems because other things simply cannot be held constant: as Garret Hardin nicely puts it, in a system, ‘we can never do merely one thing.’

Jervis sketches a few thought experiments to drive this point home. He has a nice one about the effects of external interventions on civil wars that is topical here, but I think his New York traffic example is more resonant:

In everyday thought experiments we ask what would have happened if one element in our world had been different. Living in New York, I often hear people speculate that traffic would be unbearable (as opposed to merely terrible) had Robert Moses not built his highways, bridges, and tunnels. But to try to estimate what things would have been like, we cannot merely subtract these structures from today’s Manhattan landscape. The traffic patterns, the location of businesses and residences, and the number of private automobiles that are now on the streets are in significant measure the product of Moses’s road network. Had it not been built, or had it been built differently, many other things would have been different. Traffic might now be worse, but it is also possible that it would have been better because a more efficient public transportation system would have been developed or because the city would not have grown so large and prosperous without the highways.

Substitute “invade Iraq” or “fail to invade Syria” for Moses’s bridges and tunnels, and I hope you see what I mean.

In the end, it’s much harder to get beyond banal observations about influences to strong claims about causality than our story-telling minds and the popular media that cater to them would like. Of course the invasion of Iraq in 2003 or the absence of Western military intervention in Syria have shaped the histories that followed. But what would have happened in their absence—and, by implication, what would happen now if, for example, the US now re-inserted its armed forces into Iraq or attempted to topple Assad? Those questions are far tougher to answer, and we should beware of anyone who speaks with great confidence about their answers. If you’re a social scientist who isn’t comfortable making and confident in the accuracy of your predictions, you shouldn’t be comfortable making and confident in the validity of your causal claims, either.

Five years ago, demographer Richard Cincotta claimed in a piece for Foreign Policy that a country’s age structure is a powerful predictor of its prospects for attempting and sustaining liberal democracy. “A country’s chances for meaningful democracy increase,” he wrote, “as its population ages.” Applying that superficially simple hypothesis to the data at hand, he ventured a forecast:

The first (and perhaps most surprising) region that promises a shift to liberal democracy is a cluster along Africa’s Mediterranean coast: Morocco, Algeria, Tunisia, Libya, and Egypt, none of which has experienced democracy in the recent past. The other area is in South America: Ecuador, Colombia, and Venezuela, each of which attained liberal democracy demographically “early” but was unable to sustain it. Interpreting these forecasts conservatively, we can expect there will be one, maybe two, in each group that will become stable democracies by 2020.

I read that article when it was published, and I recall being irritated by it. At the time, I had been studying democratization for more than 15 years and was building statistical models to forecast transitions to and from democracy as part of my paying job. Seen through those goggles, Cincotta’s construct struck me as simplistic to the point of naiveté. Democratization is a hard theoretical problem. States have arrived at and departed from democracy by many different pathways, so how could what amounts to a one-variable model possibly have anything useful to say about it?

Revisiting Cincotta’s work in 2014, I like it a lot more for a couple of reasons. First, I like the work better now because I have come to see it as an elegant representation of a larger idea. As Cincotta argues in that Foreign Policy article and another piece he published around the same time, demographic structure is one component of a much broader and more complex syndrome in which demography is both effect and cause. Changes in fertility rates, and through them age structure, are strongly shaped by other social changes like education and urbanization, which are correlated with, but hardly determined by, increases in national wealth.

Of course, that syndrome is what we conventionally call “development,” and the pattern Cincotta observes has a strong affinity with modernization theory. Cincotta’s innovation was to move the focus away from wealth, which has turned out to be unreliable as a driver and thus as a proxy for development in a larger sense, to demographic structure, which is arguably a more sensitive indicator of it. As I see it now, what we now call development is part of a “state shift” occurring in human society at the global level that drives and is reinforced by long-term trends in democratization and violent conflict. As in any complex system, though, the visible consequences of that state shift aren’t evenly distributed.

In this sense, Cincotta’s argument is similar to one I often find myself making about the value of using infant mortality rates instead of GDP per capita as a powerful summary measure in models of a country’s susceptibility to insurgency and civil war. The idea isn’t that dead children motivate people to attack their governments, although that may be one part of the story. Instead, the idea is that infant mortality usefully summarizes a number of other things that are all related to conflict risk. Among those things are the national wealth we can observe directly (if imperfectly) with GDP, but also the distribution of that wealth and the state’s will and ability to deliver basic social services to its citizens. Seen through this lens, higher-than-average infant mortality helps us identify states suffering from a broader syndrome that renders them especially susceptible to violent conflict.

Second, I have also come to appreciate more what Cincotta was and is doing because I respect his willingness to apply his model to generate and publish probabilistic forecasts in real time. In professional and practical terms, that’s not always easy for scholars to do, but doing it long enough to generate a real track record can yield valuable scientific dividends.

In this case, it doesn’t hurt that the predictions Cincotta made six years ago are looking pretty good right now, especially in contrast to the conventional wisdom of the late 2000s on the prospects for democratization in North Africa. None of the five states he lists there yet qualifies as a liberal democracy on his terms, a “free” designation from Freedom House). Still, it’s only 2014, one of them (Tunisia) has moved considerably in that direction, and two others (Egypt and Libya) have seen seemingly frozen political regimes crumble and substantial attempts at democratization ensue. Meanwhile, the long-dominant paradigm in comparative democratization would have left us watching for splits among ruling elites that really only happened in those places as their regimes collapsed, and many area experts were telling us in 2008 to expect more of the same in North Africa as far as the mind could see. Not bad for a “one-variable model.”

The Human Security Research Group has just published the latest in its series of now-annual reports on “trends in organized violence around the world,” and it’s essential reading for anyone deeply interested in armed conflict and other forms of political violence. You can find the PDF here.

The 2013 edition takes Steven Pinker’s Better Angels as its muse and largely concurs with Pinker’s conclusions. I’ll sheepishly admit that I haven’t read Pinker’s book (yet), so I’m not going to engage directly in that debate. Instead, I’ll call attention to what the report’s authors infer from their research about future trends in political violence. Here’s how that bit starts, on p. 18:

The most encouraging data from the modern era come from the post–World War II years. This period includes the dramatic decline in the number and deadliness of international wars since the end of World War II and the reversal of the decades-long increase in civil war numbers that followed the end of the Cold War in the early 1990s.

What are the chances that these positive changes will be sustained? No one really knows. There are too many future unknowns to make predictions with any degree of confidence.

On that point, political scientist Bear Braumoeller would agree. In an interview last year for Popular Science (here), Kelsey Atherton asked Braumoeller about Braumoeller’s assertion in a recent paper (here) that it will take 150 years to know if the downward trend in warfare that Pinker and others have identified is holding. Braumoeller replied:

Some of this literature points to “the long peace” of post-World War II. Obviously we haven’t stopped fighting wars entirely, so what they’re referring to is the absence of really really big wars like World War I and World War II. Those wars would have to be absent for like 70 to 75 more years for us to have confidence that there’s been a change in the baseline rate of really really big wars.

That’s sort of a separate question from how we know whether there are trends in warfare in general. We need to understand that war and peace are both stochastic processes. We need a big enough sample to rule out the historical average, which is about one or two big wars per century. We just haven’t had enough time since World War I and World War II to rule out the possibility that nothing’s changed.

I suspect that the authors of the Human Security Report would not dispute that claim, but after carefully reviewing Pinker’s and their own evidence, they do see causes for cautious optimism. Here I’ll quote at length, because I think it’s important to see the full array of forces taken into consideration to increase our confidence in the validity of the authors’ cautious speculations.

The case for pessimism about the global security future is well rehearsed and has considerable support within the research community. Major sources of concern include the possibility of outbreaks of nuclear terrorism, a massive transnational upsurge of lethal Islamist radicalism, or wars triggered by mass droughts and population movements driven by climate change.

Pinker notes reasons for concern about each of these potential future threats but also skepticism about the more extreme claims of the conflict pessimists. Other possible drivers of global violence include the political crises that could follow the collapse of the international financial system and destabilizing shifts in the global balance of economic and military power—the latter being a major concern of realist scholars worried about the economic and military rise of China.

But focusing exclusively on factors and processes that may increase the risks of large-scale violence around the world, while ignoring those that decrease it, also almost certainly leads to unduly pessimistic conclusions.

In the current era, factors and processes that reduce the risks of violence not only include the enduring impact of the long-term trends identified in Better Angels but also the disappearance of two major drivers of warfare in the post–World War II period—colonialism and the Cold War. Other post–World War II changes that have reduced the risks of war include the entrenchment of the global norm against interstate warfare except in self-defence or with the authority of the UN Security Council; the intensification of economic and financial interdependence that increases the costs and decreases the benefits of cross-border warfare; the spread of stable democracies; and the caution-inducing impact of nuclear weapons on relations between the major powers.

With respect to civil wars, the emergent and still-growing system of global security governance discussed in Chapter 1 has clearly helped reduce the number of intrastate conflicts since the end of the Cold War. And, at what might be called the “structural” level, we have witnessed steady increases in national incomes across the developing world. This is important because one of the strongest findings from econometric research on the causes of war is that the risk of civil wars declines as national incomes—and hence governance and other capacities—increase. Chapter 1 reports on a remarkable recent statistical study by the Peace Research Institute, Oslo (PRIO) that found that if current trends in key structural variables are sustained, the proportion of the world’s countries afflicted by civil wars will halve by 2050.

Such an outcome is far from certain, of course, and for reasons that have yet to be imagined, as well as those canvassed by the conflict pessimists. But, thanks in substantial part to Steven Pinker’s extraordinary research, there are now compelling reasons for believing that the historical decline in violence is both real and remarkably large—and also that the future may well be less violent than the past.

After reading the new Human Security Report, I remain a short-term pessimist and long-term optimist. As I’ve said in a few recent posts (see especially this one), I think we’re currently in the thick of period of systemic instability that will continue to produce mass protests, state collapse, mass killing, and other forms of political instability at higher rates than we’ve seen since the early 1990s for at least the next year or two.

At the same time, I don’t think this local upswing marks a deeper reversal of the long-term trend that Pinker identifies, and that the Human Security Report confirms. Instead, I believe that the global political economy is continuing to evolve in a direction that makes political violence less common and less lethal. This system creep is evident not only in the aforementioned trends in armed violence, but also in concurrent and presumably interconnected trends in democratization, socio-economic development, and global governance. Until we see significant and sustained reversals in most or all of these trends, I will remain optimistic about the directionality of the underlying processes of which these data can give us only glimpses.

In a recent post on Human Rights Watch’s World Policy Blog, Hanan Salah nicely summarizes the poor state of state-building in post-Qaddafi Libya:

The main problem affecting both justice and security is that armed militias still maintain the upper hand. They have various agendas—financial, territorial, political, religious—and operate with impunity two years after the Qaddafi regime ended. Successive interim governments have failed to assert control over these militias, preferring to contract them as parallel forces to the army and police. Consequently, they retain a stranglehold over key security objectives, such as protecting Libya’s oil fields, making it ever harder for the government to break their financial dependency and hold on these lucrative opportunities. The structure of the militias and related armed groups, their shared interests, political aspirations, and the tribal nature of Libyan society are further complicating factors.

This passage gets at the chicken-and-egg problem that makes state-building so hard, not just in Libya but everywhere. “Justice and security” are the chief public goods a state exists to provide, but the provision of those goods depends on widespread obedience of state authority, and that authority is hard to construct.

What bugged me about Salah’s otherwise excellent post was the use of the verb “prefer” to indicate why this authority isn’t cohering faster in Libya. “Prefer” connotes choice, and I’m not convinced that the officials comprising Libya’s internationally recognized government have very much of that. They face an array of entrenched militias that are probably profiting handsomely from control of their various fiefdoms. Those officials supposedly command an army and police force of their own, but those organizations are still small and under-resourced. Worse, the revenue streams that could make the national army and state police stronger—including oil—are often controlled by the very militias those forces are supposed to be beefing up to defeat. Under these circumstances, how exactly are Libyan officials supposed to persuade these militias to cooperate? Give them a stern talking-to?

To be fair, Salah’s post is hardly the first place I’ve seen this line. Actually, I think it’s fair to say that this is comparative politics’ version of the Green Lantern Theory that Matt Yglesias coined to describe neoconservative U.S. foreign policy and Brendan Nyhan has since extended to the American presidency. In the Green Lantern Theory, political outcomes are mostly a matter of will. If the state doesn’t cohere, it’s because the people tasked with doing it lack the spine to fulfill their charge as duly chosen leaders.

If we reject the Green Lantern Theory of state-building and recognize that power is at least as important as will, it’s tempting to think that outsiders can goose the process with an infusion of armed forces, or at least the money and training an internationally recognized government needs to build up its own. The growth of the state is stunted, so a few costly doses of hormone therapy should do the trick. In fact, as Reuters reported, Libya’s prime minister recently made just this plea at an investment conference in London:

If the international community does not help in the collection of arms and ammunition, if we don’t get help in forming the army and the police, things are going to take very long… The situation is not going to improve unless we get real and practical assistance.

In fact, politics isn’t nearly as mechanical and modular as this idea implies. Before embarking on a new state-boosting mission in Libya, foreign governments would do well to take another look at Somalia, which has been the target of similar treatments for the past two decades. As Alex de Waal describes in a recent post on the LRB Blog,

[President] Hassan’s Western backers have not yet squared the circle of pouring money and guns into a client government to fight a counterinsurgency, and preventing that government from becoming rentierist, militaristic and corrupt. Rent-seeking pervades the whole system: the president or defence minister must bargain separately with each military unit to secure its loyalty for each operation. And even then, he cannot order a Somali unit to enter a ‘liberated’ town where the locals won’t welcome it. It’s no surprise that Somalis hedge their bets against the time when the [Somali Federal Government’s] international sponsors tire of a Sisyphean counterinsurgency and sell out their erstwhile proxies. Even if al-Shabab were defeated, it wouldn’t solve Somalia’s problems. The corrupt rentierist system of government, which gave rise to al-Shabab in the first place, would be more entrenched than before.

And this is the Great Frustration of applied social science: prescription doesn’t always follow from explanation. Even if we can understand pretty well why state-building is so hard, we still can’t figure out how to control it. Whether that’s a curse or a blessing will depend on whom you ask, and therein lies the essence of politics.

In the Central African Republic, an assemblage of rebel groups has toppled the government and installed a new one but now refuses to follow its writ. As those rebels loot and maraud, new armed groups have formed to resist them, and militias loyal to the old government have struck back, too. All of this has happened on the watch of a 2,000-person peacekeeping force from neighboring states. With U.N. backing, those neighbors are now sending more men with guns in hopes that another 1,500 soldiers will finally help restore some sense of order.

As the very act of listing implies, we often think of these situations as discrete cases. In our social-scientific imaginations, countries are a bit like petri dishes lined up on a laboratory countertop. Each undergoes a similar set of experiments, and our job is to explain the diversity of their outcomes.

The longer I watch world affairs, though, the less apt that experimental metaphor seems. We can only really understand processes like state collapses—and the civil wars that usually produce them, and the regime transformations that often precede and succeed them, and virtually everything else we study in international studies—by thinking of these “cases” as local manifestations of system-level dynamics, or at least the product of interactions between local and global processes that are inseparable and mutually causal.

If we think on a systemic scale, it’s easier to see that we are now living through a period of global disorder matched in recent history only by the years surrounding the disintegration of the Soviet Union, and possibly exceeding it. Importantly, it’s not just the spate of state collapses through which this disorder becomes evident, but also the wider wave of protest activity and institutional transformation to which some of those collapses are connected. These streams of change are distinct in some ways, but they also shape each other and share some common causes.

And what are those common causes? The 2007 financial crisis surely played a significant role. The resulting recessions in the U.S. and Europe rippled outward, shrinking trade flows and remittances to smaller and poorer countries and pulling down demand for commodities on which some of their economies heavily depend.

Those recessions also seem to have accelerated shifts in relative power among larger countries, or at least perceptions of them. Those perceptions—see here and here, for example—may matter even more than the underlying reality because they shape governments’ propensity to intervene abroad, the forms those interventions take, and, crucially, other governments’ beliefs about what kinds of intervention might occur in the future. In this instance, those perceptions have only been reinforced by popular concerns about the cost and wisdom of foreign intervention when so many are suffering through hard times at home. This amalgamation of forces seems to have found its sharpest expression yet in the muddled and then withdrawn American threat to punish the Syrian regime for its use of chemical weapons, but the trends that crystallized in that moment have been evident for a while.

The financial crisis also coincided with, and contributed to, a global run-up in food prices that still hasn’t abated by much (see the chart below, from the FAO). As I mentioned in another recent post, a growing body of evidence supports the claim that high food prices help produce waves of civil unrest. This link is evident at the level of the global system and in specific cases, from the countries involved in the Arab Spring to South Africa. Because food prices are so influential, I think it’s likely that climate change is contributing to the current disorder, too, as another force putting upward pressure on those prices and sometimes dislodging large numbers of people who have to pay them.

As Peter Turchin and others have argued, it’s possible that generic oscillations in human social order—perhaps the political analogue of the business cycle—are also part of the story. I’m not confident that these patterns are distinct from the forces I’ve already mentioned, but they could be, at least in part. In any case, those patterns seem sufficiently robust that they deserve more attention than most of us give them now.

Last but not least, the systemic character of these processes is also evident in the forms of negative and positive feedback that arise to try to reverse or accelerate the slide into entropy. Powerful players with a stake in extant structures—mostly states, but also private corporations and even transnational NGOs—work to restore local forms of order that reinforce rather than challenge those structures. At the same time, other actors try to leverage the entropy to their own advantage. Governments less invested in the prior order may see new opportunities to weaken rivals or husband allies. Transnational criminal enterprises often find ways to expand revenue streams and develop new ones by smuggling arms and other contraband to and through societies that have fallen apart. Since the late 2000s, for example, “there has been a significant increase in the number of attacks on vessels by pirates,” Interpol claims, and I don’t think this concurrence of this trend with the spikes in popular unrest and state collapse is purely coincidental.

This system-level view finds linkages between a host of recent trends that we usually only consider in isolation from each other. It also suggests that this, too, shall pass—and then occur again. If Turchin & co. are correct, the current wave of disorder won’t peak for another several years, and we can expect the next iteration to arrive in the latter half of the current century. I’m not convinced the cycles are as tidy as that, and I wonder if the nature of the system itself is now changing in ways that will produce new patterns in the future. Either way, though, I hope it’s now clear that the miseries besetting CAR aren’t as disconnected from the collapses of Libya, Syria, and Yemen or the eruptions of mass protest in a host of countries over the past several years as our compartmentalized reading and theorizing usually entices us to think.

I’m almost finished reading Michael Pollan’s latest, Cooked. It’s a terrific book about food, but it’s also steeped in science, and I wanted to share a passage from the part of the book on fermentation that really resonated with me. Pollan is writing about microbiology, but the developments he identifies in that field could (or should) apply just as well to the social sciences. The passage starts like this:

In the decades since Louis Pasteur founded microbiology, medical research has focused mainly on bacteria’s role in causing disease. The bacteria that reside in and on our bodies were generally regarded as either harmless “commensals”—freeloaders, basically—or pathogens to be defended against. Scientists tended to study these bugs one at a time, rather than as communities. This was partly a deeply ingrained habit of reductive science, and partly a function of the available tools. Scientists naturally focused their attention on the bacteria they see, which meant the handful of individual bugs that could be cultivated in a petri dish. There, they found some good guys and some bad guys. But the general stance toward bacteria we had discovered all around us was shaped by metaphors of war, and in that war, antibiotics became the weapon of choice.

The “habit of reductive science” Pollan describes should be familiar to social scientists, too. We often sort the objects of our analysis into binary categories of helpful and hurtful, assume the objects we see are all there really is, and then design interventions to try to kill the bad without harming the good. Where microbiology has traditionally drawn a sharp line between pathogens and cells that belong, social science has neatly distinguished rebel groups and criminal gangs and patronage networks from bureaucracies and political parties and civil society. Where medicine has antibiotics, development practitioners have aid.

What we’re now learning, though, is that these lines are really much blurrier than we’ve assumed. Pollan goes on:

But it turns out that the overwhelming majority of bacteria residing in the gut simply refuse to grow on a petri dish—a phenomenon known among researchers as “the great plate anomaly.” Without realizing it, they were practicing what is sometimes called parking-lot science—named for the human tendency to search for lost keys under the streetlights not because that’s where we lost them but because that is where we can best see. The petri dish was a streetlight. But when, in the early 2000s, researchers developed genetic “batch” sequencing techniques allowing them to catalog all the DNA in a sample of soil, say, or seawater or feces, science suddenly acquired a broad and powerful beam light that could illuminate the entire parking lot. When it did, we discovered hundreds of new species in the human gut doing all sorts of unexpected things.

This, to me, is the promise of what Gary King calls the “social science data revolution.” Exponential growth in the production and distribution of information to and from all parts of the world, and in our collective capacity to store and process and analyze that information, are to the social sciences what genetic batch sequencing is to microbiology. Our libraries and limited professional networks were our petri dishes, and now they’ve been shattered—in a good way.

Pollan then describes where microbiology’s version of the data revolution has led:

To their surprise, microbiologists discovered that nine of every ten cells in our bodies do not belong to us, but to these microbial species (most of them residents of our gut), and that 99 percent of the DNA we’re carrying around belongs to those microbes. Some scientists, trained in evolutionary biology, began looking at the human individual in a humbling new light: as a kind of superorganism, a community of several hundred coevolved and interdependent species. War metaphors no longer made sense. So the microbiologists began borrowing new metaphors from the ecologists.

I’d say a comparable gestalt shift is occurring in some corners of social science, with similarly dramatic implications. For decades, we’ve cranked out snapshots and diagrams and typologies of objects—states, parties, militaries, ethnic groups—that we’ve assumed to be more or less static and distinct and told just-so stories about how one thing changes into another. Now, we’re shedding those functionalist assumptions and getting better at seeing those objects as permeable superorganisms embedded in ecosystems, all of them continually coevolving in ways that may elude our capacity to narrate, or even to understand at all. The implications are simultaneously thrilling and overwhelming.

According to today’s Washington Post, the U.S. government is starting to supply food and medicine directly to selected Syrian rebel groups. Meanwhile, “Britain and other nations working in concert with the United States are expected to go further to help the rebel Free Syrian Army by providing battlefield equipment such as armored vehicles, night-vision devices or body armor.”

The point of all this assistance, of course, is to hasten the fall of Syrian President Bashir al-Assad. According to newly minted Secretary of State John Kerry, Assad is “out of time and must be out of power.”

Best I can tell, the logic behind this stepped-up support for the Syrian rebels Western governments “like” follows the logic of an assembly line. To increase desired outputs, increase relevant inputs.

But civil wars aren’t like factories. They’re more like ecosystems, and if there’s one thing we’ve learned from our attempts to manage ecosystems, it’s that they often have unintended consequences. Consider this 2009 story from the New York Times:

With its craggy green cliffs and mist-laden skies, Macquarie Island — halfway between Australia and Antarctica — looks like a nature lover’s Mecca. But the island has recently become a sobering illustration of what can happen when efforts to eliminate an invasive species end up causing unforeseen collateral damage.

In 1985, Australian scientists kicked off an ambitious plan: to kill off non-native cats that had been prowling the island’s slopes since the early 19th century. The program began out of apparent necessity — the cats were preying on native burrowing birds. Twenty-four years later, a team of scientists from the Australian Antarctic Division and the University of Tasmania reports that the cat removal unexpectedly wreaked havoc on the island ecosystem.

“Our findings show that it’s important for scientists to study the whole ecosystem before doing eradication programs,” said Arko Lucieer, a University of Tasmania remote-sensing expert and a co-author of the paper. “There haven’t been a lot of programs that take the entire system into account. You need to go into scenario mode: ‘If we kill this animal, what other consequences are there going to be?’”

I don’t mean to suggest a moral equivalence between the human beings fighting and being murdered in Syria and the rabbits and cats and birds on Macquarie Island. I do mean to suggest that attempts to manipulate systems like these almost always underestimate the complexity of the problem. What scientist Barry Rice said to the New York Times for that 2009 article on the difficulty of managing invasive species applies just as well to attempts by outside powers to manufacture desired outcomes in civil wars:

When you’re doing a removal effort, you don’t know exactly what the outcome will be. You can’t just go in and make a single surgical strike. Every kind of management you do is going to cause some damage.

I hope Syria gets to a better place soon. Like Dan Trombly and Ahsan Butt, however, I am not confident that increased support for selected rebel factions will help that happen, and I am worried about the unintended consequences it will bring.